Hi, today I would like to share with you a great talk given by Lisa McInnes-Smith on the TEDx Melbourne in 2015 I believe. I received a link for her performance from a very good friend who wants to point out that you only learn when the pain is involved in the process. Thanks! p ;).
Hi, today again I advise my good friend what to do with his career journey. Again, and it seems to me that I am becoming more and more the Coach and the Mentor to people than just software creator and technical expert. I want to write about the career advisor role I sometimes got to some of my friends. The thing is that when I was at the beginning of my career I was looking for the Continue ReadingCareer Advisor
Hi, Today I would like to announce that my GitHub fork at https://github.com/sowson/darknet has a new update, the fork is an advanced port of DarkNet CNN from CUDA to OpenCL and tested on macOS with eGPU from Sonnet named Breakaway RX 570 Puck and on my GreenPC it also supports Intel Iris GPU, OpenCV 3, and there are several use cases for it. Yolo3, Yolo2, Yolo1, CIFAR-10 solutions work fine, using demo from webcam also, from mp4 videos Continue ReadingDarkNet in OpenCL
Hi, Today I would like to announce that my GitHub fork at https://github.com/sowson/darknet has a new update, the fork is an advanced port of DarkNet CNN from CUDA to OpenCL and tested on macOS with eGPU from Sonnet named Breakaway RX 570 Puck and on my GreenPC. Let’s get started the training by the inspiration from the solution original author Joseph Redmon given the TED talk. Interested how it works and how to rebuild? Why I spent some Continue ReadingDarkNet Training
Hi, Today I would like to announce that my GitHub fork at https://github.com/sowson/darknet has a new update, the fork is a advanced port of DarkNet CNN from CUDA to OpenCL and tested on macOS with eGPU from Sonnet named Breakaway RX 570 Puck. You can enjoy my coding work on this subject by cloning the GIT repository. I only want to show you two pictures of detections on my GreenPC. YoloV2 [gamer@dreampc darknet]$ ./darknet detect cfg/yolov2.cfg ../../weights/yolov2.weights data/dog.jpgDevice Continue ReadingDarkNet CNN in OpenCL on macOS with Yolo3
Yes, I know that it is impossible to predict lottery results. But if the results would be predictable? Of course I know they are not, but just hypothetically for a play with Perceptron Neural Network and prediction algorithms I want to show you that in 256 ;-) lines of code you are able to play with prediction thanks to EnCog 3.4 library. I bought recently 2 Jeff Heaton’s books about neural networks and C# and his library. Continue ReadingEuroJackpot with EnCog ANN and Stats
Hi, today I will instead of any new idea, show you my latest upgraded DreamPC. I used it for some time to Image Recognition and it works quite well. Once I was involved by myself into self-study about Convutional Neural Networks and the C code I used CentOS GNU/Linux, but now I bring it back. I want to share the spec, it is not so impressive I believe. But it is enough to play all games I Continue ReadingGreen PC
Hi, First welcome in 2018 on my blog, I hope you all feel exited in the new year like me, sorry to be silent for a while, but I was absorbing my first GitHub fork wich is “sowson/darknet” and I was coding like a crazy one. Still I have several todo on this code but I really like it. And regarding to this journey, Today I would like to share with you something really awesome that I Continue ReadingFloating Pointers on OpenCL cl_mem
Hi, today I would like to share with you truly amazing solution. It was originally presented on TED Talks about DarkNet by Joseph Redmon. Once I saw it I was wonder how to play with this solution on my MacBook Pro 13 that as you may know has not GPU I am mean it has but not very strong. But that was improved once I bought Sonnet eGFX 580 Puck… the funny thing is that they called Continue ReadingCar See by DarkNet CNN on MacBookPro 13 with Sonnet eGFX 580
Sorry, I do not know how to play, I just love Piano sound… ;-). Do you like it? I will play anyway… ;-). p ;).